A study of the role of nitric oxide in the mechanism of action of hydroalcoholic extract of saffron (Crocus sativus) on the electrophysiological properties of the rabbit atrioventricular node

Biologically active substances of plant origin represent an essential branch of modern cardiovascular pharmacotherapy. Furthermore, drugs of plant origin have the advantage of weaker adverse effects and lower prices than synthetic drugs. Pharmacological studies and traditional medical literature point to the anti-ischemic and hypotensive effects of the Crocus sativus L. (Iridacea). The major goals of the present study were: (1) to determine the negative dormotrophic properties of a hydroalcoholic extract of saffron on an isolated AV node and (2) to establish the role of nitric oxide in the mediating effects of saffron on the electrophysiological properties of the AV node. This was an experimental study. Selective stimulation protocols were used to independently quantify AV nodal recovery, facilitation and fatigue. We used isolated perfused rabbit AV node preparation, in three groups (N=32); in each group, we assessed the plant's effect in comparison with the control. In the pilot study, we used different concentrations (A=9 x 10-2 mg/L, B=19 x 10-2 mg/L and C=27 x 10-2 mg/L) to select the optimum concentration (19 x 10-2 mg/L) of the hydroalcoholic extract of saffron. Saffron has a depressant effect on basic and rate-dependent properties of the AV node. We observed an increasing AVCT (38.8 ±4 to 41.7 ±4 msec) and FRP (157.6 ±3 to 163.7 ±4 msec). Also saffron increased the amount of facilitation and the magnitude of fatigue (5.9 ±0.3 to 11.1 ±1 msec). The NOS inhibitor (L-NAME) has a preventative effect on the depressant effect of saffron on AVCT and FRP

Contributions of anterior cingulate cortex and basolateral amygdala to decision confidence and learning under uncertainty.

The subjective sense of certainty, or confidence, in ambiguous sensory cues can alter the interpretation of reward feedback and facilitate learning. We trained rats to report the orientation of ambiguous visual stimuli according to a spatial stimulus-response rule that must be learned. Following choice, rats could wait a self-timed delay for reward or initiate a new trial. Waiting times increase with discrimination accuracy, demonstrating that this measure can be used as a proxy for confidence. Chemogenetic silencing of BLA shortens waiting times overall whereas ACC inhibition renders waiting times insensitive to confidence-modulating attributes of visual stimuli, suggesting contribution of ACC but not BLA to confidence computations. Subsequent reversal learning is enhanced by confidence. Both ACC and BLA inhibition block this enhancement but via differential adjustments in learning strategies and consistent use of learned rules. Altogether, we demonstrate dissociable roles for ACC and BLA in transmitting confidence and learning under uncertainty

Stimulation of oxytocin receptor during early reperfusion period protects the heart against ischemia/reperfusion injury: The role of mitochondrial ATP-sensitive potassium channel, nitric oxide, and prostaglandins

Postconditioning is a simple and safe strategy for cardioprotection and infarct size limitation. Our previous study showed that oxytocin (OT) exerts postconditioning effect on ischemic/reperfused isolated rat heart. The aim of this study was to investigate the involvement of OT receptor, mitochondrial ATP-sensitive potassium channel (mKATP), nitric oxide (NO) and cyclooxygenase (COX) pathways in OT postconditioning. Isolated rat hearts were divided into10 groups and underwent 30 min of regional ischemia followed by 120 min of reperfusion (n =6). In I/R (ischemia/reperfusion) group, ischemia and reperfusion were induced without any treatment. In OT group, oxytocin was perfused 5 min prior to beginning of reperfusion for 25 min. In groups 3-6, atosiban (oxytocin receptor blocker), L-NAME (N-Nitro-L-Arginine Methyl Ester, non-specific nitric oxide synthase inhibitor), 5-HD (5-hydroxydecanoate, mKATP inhibitor) and indomethacin (cyclooxygenase inhibitor) were infused prior to oxytocin administration. In others, the mentioned inhibitors were perfused prior to ischemia without oxytocin infusion. Infarct size, ventricular hemodynamic, coronary effluent, malondialdehyde (MDA) and lactate dehydrogenase (LDH) were measured at the end of reperfusion. OT perfusion significantly reduced infarct size, MDA and LDH in comparison with IR group. Atosiban, 5HD, L-NAME and indomethacin abolished the postconditioning effect of OT. Perfusion of the inhibitors alone prior to ischemia had no effect on infarct size, hemodynamic parameters, coronary effluent and biochemical markers as compared with I/R group. In conclusion, this study indicates that postconditioning effects of OT are mediated by activation of mKATP and production of NO and Prostaglandins (PGs). © 2015 Tehran University of Medical Sciences. All rights reserved

Stakeholders’ impact on the reuse potential of structural elements at the end-of-life of a building: A machine learning approach

The construction industry, and at its core the building sector, is the largest consumer of non-renewable resources, which produces the highest amount of waste and greenhouse gas emissions worldwide. Since most of the embodied energy and CO2 emissions during the construction and demolition phases of a building are related to its structure, measures to extend the service life of these components should be prioritised. This study develops a set of easy-to-understand instructions to facilitate the practitioners in assessing the social sustainability and responsibility of reusing the load-bearing structural components within the building sector. The results derived by developing and then employing advanced machine learning techniques indicate that the most significant social factor is the perception of the regulatory authorities. The second and third ranks among the social reusability factors belong to risks. Since there is a strong correlation between perception and risk, the potential risks associated with reusing structural elements affect the stakeholders’ perception of reuse. The Bayesian network developed in this study unveil the complex and non-linear correlation between variables, which means none of the factors could alone determine the reusability of an element. This paper shows that by using the basics of probability theory and combining them with advanced supervised machine learning techniques, it is possible to develop tools that reliably estimate the social reusability of these elements based on influencing variables. Therefore, the authors propose using the developed approach in this study to promote materials' circularity in different construction industry sub-sectors

Methylation of O6-methyl guanine methyltransferase gene promoter in meningiomas - comparison between tumor grades I, II, and III

Background: Meningiomas are the second most common primary intracranial tumors after gliomas. Epigenetic biomarkers such as DNA methylation, which is found in many tumors and is thus important in tumorigenesis can help diagnose meningiomas and predict response to adjuvant chemotherapy. We investigated aberrant O6- methyl guanine methyltransferase (MGMT) methylation in meningiomas. Materials and Methods: Sixty-one patients were classified according to the WHO grading, and MGMT promoter methylation status was examined via the methylation-Specific PCR(MSP) method. Results: MGMT promoter methylation was found in 22.2 of grade I, 35 of grade I with atypical features, 36 of grade II, and 42.9 of grade III tumors. Conclusions: There was an increase, albeit not statistically significant, in MGMT methylation with a rise in the tumor grade. Higher methylation levels were also observed in the male gender

Review of factors resulting in systemic biases in the screening, assessment, and treatment of individuals at clinical high-risk for psychosis in the United States

BACKGROUND: Since its inception, research in the clinical high-risk (CHR) phase of psychosis has included identifying and exploring the impact of relevant socio-demographic factors. Employing a narrative review approach and highlighting work from the United States, sociocultural and contextual factors potentially affecting the screening, assessment, and service utilization of youth at CHR were reviewed from the current literature. RESULTS: Existing literature suggests that contextual factors impact the predictive performance of widely used psychosis-risk screening tools and may introduce systemic bias and challenges to differential diagnosis in clinical assessment. Factors reviewed include racialized identity, discrimination, neighborhood context, trauma, immigration status, gender identity, sexual orientation, and age. Furthermore, racialized identity and traumatic experiences appear related to symptom severity and service utilization among this population. CONCLUSIONS: Collectively, a growing body of research from the United States and beyond suggests that considering context in psychosis-risk assessment can provide a more accurate appraisal of the nature of risk for psychosis, render more accurate results improving the field\u27s prediction of conversion to psychosis, and enhance our understanding of psychosis-risk trajectories. More work is needed in the U.S. and across the globe to uncover how structural racism and systemic biases impact screening, assessment, treatment, and clinical and functional outcomes for those at CHR

Integration of hybridization-based markers (overgos) into physical maps for comparative and evolutionary explorations in the genus Oryza and in Sorghum

BACKGROUND: With the completion of the genome sequence for rice (Oryza sativa L.), the focus of rice genomics research has shifted to the comparison of the rice genome with genomes of other species for gene cloning, breeding, and evolutionary studies. The genus Oryza includes 23 species that shared a common ancestor 8–10 million years ago making this an ideal model for investigations into the processes underlying domestication, as many of the Oryza species are still undergoing domestication. This study integrates high-throughput, hybridization-based markers with BAC end sequence and fingerprint data to construct physical maps of rice chromosome 1 orthologues in two wild Oryza species. Similar studies were undertaken in Sorghum bicolor, a species which diverged from cultivated rice 40–50 million years ago. RESULTS: Overgo markers, in conjunction with fingerprint and BAC end sequence data, were used to build sequence-ready BAC contigs for two wild Oryza species. The markers drove contig merges to construct physical maps syntenic to rice chromosome 1 in the wild species and provided evidence for at least one rearrangement on chromosome 1 of the O. sativa versus Oryza officinalis comparative map. When rice overgos were aligned to available S. bicolor sequence, 29% of the overgos aligned with three or fewer mismatches; of these, 41% gave positive hybridization signals. Overgo hybridization patterns supported colinearity of loci in regions of sorghum chromosome 3 and rice chromosome 1 and suggested that a possible genomic inversion occurred in this syntenic region in one of the two genomes after the divergence of S. bicolor and O. sativa. CONCLUSION: The results of this study emphasize the importance of identifying conserved sequences in the reference sequence when designing overgo probes in order for those probes to hybridize successfully in distantly related species. As interspecific markers, overgos can be used successfully to construct physical maps in species which diverged less than 8 million years ago, and can be used in a more limited fashion to examine colinearity among species which diverged as much as 40 million years ago. Additionally, overgos are able to provide evidence of genomic rearrangements in comparative physical mapping studies

Using Machine Learning Algorithms to Develop a Clinical Decision-Making Tool for COVID-19 Inpatients.

BACKGROUND: Within the UK, COVID-19 has contributed towards over 103,000 deaths. Although multiple risk factors for COVID-19 have been identified, using this data to improve clinical care has proven challenging. The main aim of this study is to develop a reliable, multivariable predictive model for COVID-19 in-patient outcomes, thus enabling risk-stratification and earlier clinical decision-making. METHODS: Anonymised data consisting of 44 independent predictor variables from 355 adults diagnosed with COVID-19, at a UK hospital, was manually extracted from electronic patient records for retrospective, case-control analysis. Primary outcomes included inpatient mortality, required ventilatory support, and duration of inpatient treatment. Pulmonary embolism sequala was the only secondary outcome. After balancing data, key variables were feature selected for each outcome using random forests. Predictive models were then learned and constructed using Bayesian networks. RESULTS: The proposed probabilistic models were able to predict, using feature selected risk factors, the probability of the mentioned outcomes. Overall, our findings demonstrate reliable, multivariable, quantitative predictive models for four outcomes, which utilise readily available clinical information for COVID-19 adult inpatients. Further research is required to externally validate our models and demonstrate their utility as risk stratification and clinical decision-making tools

Quantitative miRNA Expression Analysis Using Fluidigm Microfluidics Dynamic Arrays

MicroRNA (miRNA) is a small non-coding RNA that can regulate gene expression in both plants and animals. Studies showed that miRNAs play a critical role in human cancer by targeting messenger RNAs that are positive or negative regulators of cell proliferation and apoptosis. Here, we evaluated miRNA expression in formalin fixed, paraffin embedded (FFPE) samples and fresh frozen (FF) samples using a high throughput qPCR-based microfluidic dynamic array technology (Fluidigm). We compared the results to hybridization-based microarray platforms using the same samples. We obtained a highly correlated Ct values between multiplex and single-plex RT reactions using standard qPCR assays for miRNA expression. For the same samples, the microfluidic technology (Fluidigm 48.48 dynamic array systems) resulted in a left shift towards lower Ct values compared to those observed by standard TaqMan (ABI 7900HT, mean difference, 3.79). In addition, as little as 10ng total RNA was sufficient to reproducibly detect up to 96 miRNAs at a wide range of expression values using a single 96-multiplexing RT reaction in either FFPE or FF samples. Comparison of miRNAs expression values measured by microfluidic technology with those obtained by other array and Next Generation sequencing platforms showed positive concordance using the same samples but revealed significant differences for a large fraction of miRNA targets. The qPCRarray based microfluidic technology can be used in conjunction with multiplexed RT reactions for miRNA gene expression profiling. This approach is highly reproducible and the results correlate closely with the existing singleplex qPCR platform while achieving much higher throughput at lower sample input and reagent usage. It is a rapid, cost effective, customizable array platform for miRNA expression profiling and validation. However, comparison of miRNA expression using different platforms requires caution and the use of multiple platforms

Multiple Analytical Approaches Reveal Distinct Gene-Environment Interactions in Smokers and Non Smokers in Lung Cancer

Complex disease such as cancer results from interactions of multiple genetic and environmental factors. Studying these factors singularly cannot explain the underlying pathogenetic mechanism of the disease. Multi-analytical approach, including logistic regression (LR), classification and regression tree (CART) and multifactor dimensionality reduction (MDR), was applied in 188 lung cancer cases and 290 controls to explore high order interactions among xenobiotic metabolizing genes and environmental risk factors. Smoking was identified as the predominant risk factor by all three analytical approaches. Individually, CYP1A1*2A polymorphism was significantly associated with increased lung cancer risk (OR = 1.69;95%CI = 1.11–2.59,p = 0.01), whereas EPHX1 Tyr113His and SULT1A1 Arg213His conferred reduced risk (OR = 0.40;95%CI = 0.25–0.65,p<0.001 and OR = 0.51;95%CI = 0.33–0.78,p = 0.002 respectively). In smokers, EPHX1 Tyr113His and SULT1A1 Arg213His polymorphisms reduced the risk of lung cancer, whereas CYP1A1*2A, CYP1A1*2C and GSTP1 Ile105Val imparted increased risk in non-smokers only. While exploring non-linear interactions through CART analysis, smokers carrying the combination of EPHX1 113TC (Tyr/His), SULT1A1 213GG (Arg/Arg) or AA (His/His) and GSTM1 null genotypes showed the highest risk for lung cancer (OR = 3.73;95%CI = 1.33–10.55,p = 0.006), whereas combined effect of CYP1A1*2A 6235CC or TC, SULT1A1 213GG (Arg/Arg) and betel quid chewing showed maximum risk in non-smokers (OR = 2.93;95%CI = 1.15–7.51,p = 0.01). MDR analysis identified two distinct predictor models for the risk of lung cancer in smokers (tobacco chewing, EPHX1 Tyr113His, and SULT1A1 Arg213His) and non-smokers (CYP1A1*2A, GSTP1 Ile105Val and SULT1A1 Arg213His) with testing balance accuracy (TBA) of 0.6436 and 0.6677 respectively. Interaction entropy interpretations of MDR results showed non-additive interactions of tobacco chewing with SULT1A1 Arg213His and EPHX1 Tyr113His in smokers and SULT1A1 Arg213His with GSTP1 Ile105Val and CYP1A1*2C in nonsmokers. These results identified distinct gene-gene and gene environment interactions in smokers and non-smokers, which confirms the importance of multifactorial interaction in risk assessment of lung cancer